Francisco M. De La Vega, Brooke Rhead, Yannick Pouliot, Justin Guinney
The incidence and mortality of cancer vary widely across race and ethnicity. Such variation is influenced by socioeconomic factors, environmental exposures, and genetic background. Individuals of non-European descent are underrepresented in cancer genomic studies, which limits a comprehensive understanding of disparities in the diagnosis, prognosis, and treatment of cancer among these populations. Furthermore, the social constructs of race and ethnicity are far from precise categories to understand the biological underpinnings of such differences.
In this study, we use a large real-world data (RWD) patient cohort to examine associations of genetic ancestry with somatic alterations in cancer driver genes. We inferred genetic ancestry from approximately 100,000 de-identified records of patients with diverse histology who underwent tumor genomic profiling with the Tempus xT 648-gene next-generation sequencing (NGS) assay. We selected 654 ancestry informative markers that overlap the capture regions of the assay to infer global ancestry proportions at the continental level: Africa (AFR), America (AMR), Europe (EUR), East Asia (EAS), and South Asia (SAS).
While most patients are of European descent (72%), our cohort includes 8 to 12-fold more patients with substantial (>50%) non-European ancestry than TCGA. Logistic regression was used to examine associations between continental ancestry proportions and presence of nonsynonymous somatic mutations and copy number alterations (CNA) in cancer genes, controlling for assay version, gender and age. P-values were adjusted for multiple testing by the Benjamini-Hochberg method to control the false discovery rate at 5%. We identify 7 significant associations with small somatic mutations and 15 with CNAs with non-European ancestries (all p<0.0001). Among others, we found associations between small somatic mutations in CTNNB1 with EAS ancestry (OR=1.44; odds per 20% increase in given ancestry proportion), EGFR with EAS (OR=1.49) and AMR (OR=1.78) ancestries in lung cancer, and ASXL1 with AMR ancestry in brain cancer (OR=2.48). Furthermore, we identified several associations between ancestry and CNAs: MTAP with AMR (OR=1.45) and EGFR with SAS (OR=1.46) in lung cancer, among others. Finally, we observed a reduction in actionable mutations (OncoKB levels 1, 2, and R1) with AFR ancestry in BRAF (OR=0.73) and EGFR (0.77) in colorectal and lung cancers, correspondingly.
Our results support the use of genetic ancestry inference on RWD to improve upon the use of race and ethnicity to better understand the impact of ancestry on mutational processes that influence cancer incidence, progression, and outcomes.
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